diff --git a/src/memory/batch-gemini.test.ts b/src/memory/batch-gemini.test.ts
index 67d90a5a78b..57bc71291b9 100644
--- a/src/memory/batch-gemini.test.ts
+++ b/src/memory/batch-gemini.test.ts
@@ -75,9 +75,11 @@ describe("runGeminiEmbeddingBatches", () => {
       requests: [
         {
           custom_id: "req-1",
-          content: { parts: [{ text: "hello world" }] },
-          taskType: "RETRIEVAL_DOCUMENT",
-          outputDimensionality: 1536,
+          request: {
+            content: { parts: [{ text: "hello world" }] },
+            taskType: "RETRIEVAL_DOCUMENT",
+            outputDimensionality: 1536,
+          },
         },
       ],
       wait: true,
diff --git a/src/memory/batch-gemini.ts b/src/memory/batch-gemini.ts
index 111570a998c..3afb5121ff7 100644
--- a/src/memory/batch-gemini.ts
+++ b/src/memory/batch-gemini.ts
@@ -5,15 +5,13 @@ import {
 } from "./batch-runner.js";
 import { buildBatchHeaders, normalizeBatchBaseUrl } from "./batch-utils.js";
 import { debugEmbeddingsLog } from "./embeddings-debug.js";
-import type { GeminiEmbeddingClient } from "./embeddings-gemini.js";
+import type { GeminiEmbeddingClient, GeminiTextEmbeddingRequest } from "./embeddings-gemini.js";
 import { hashText } from "./internal.js";
 import { withRemoteHttpResponse } from "./remote-http.js";
 
 export type GeminiBatchRequest = {
   custom_id: string;
-  content: { parts: Array<{ text: string }> };
-  taskType: "RETRIEVAL_DOCUMENT" | "RETRIEVAL_QUERY";
-  outputDimensionality?: number;
+  request: GeminiTextEmbeddingRequest;
 };
 
 export type GeminiBatchStatus = {
@@ -83,13 +81,7 @@ async function submitGeminiBatch(params: {
     .map((request) =>
       JSON.stringify({
         key: request.custom_id,
-        request: {
-          content: request.content,
-          taskType: request.taskType,
-          ...(typeof request.outputDimensionality === "number"
-            ? { outputDimensionality: request.outputDimensionality }
-            : {}),
-        },
+        request: request.request,
       }),
     )
     .join("\n");
diff --git a/src/memory/embeddings-gemini.test.ts b/src/memory/embeddings-gemini.test.ts
index 451ebd795da..36cb6bfd111 100644
--- a/src/memory/embeddings-gemini.test.ts
+++ b/src/memory/embeddings-gemini.test.ts
@@ -3,6 +3,7 @@ import * as authModule from "../agents/model-auth.js";
 import {
   buildFileDataPart,
   buildGeminiParts,
+  buildGeminiTextEmbeddingRequest,
   buildInlineDataPart,
   createGeminiEmbeddingProvider,
   DEFAULT_GEMINI_EMBEDDING_MODEL,
@@ -90,6 +91,24 @@ describe("buildFileDataPart", () => {
   });
 });
 
+describe("buildGeminiTextEmbeddingRequest", () => {
+  it("builds a text embedding request with optional model and dimensions", () => {
+    expect(
+      buildGeminiTextEmbeddingRequest({
+        text: "hello",
+        taskType: "RETRIEVAL_DOCUMENT",
+        modelPath: "models/gemini-embedding-2-preview",
+        outputDimensionality: 1536,
+      }),
+    ).toEqual({
+      model: "models/gemini-embedding-2-preview",
+      content: { parts: [{ text: "hello" }] },
+      taskType: "RETRIEVAL_DOCUMENT",
+      outputDimensionality: 1536,
+    });
+  });
+});
+
 // ---------- Model detection ----------
 
 describe("isGeminiEmbedding2Model", () => {
@@ -255,6 +274,28 @@ describe("gemini-embedding-2-preview provider", () => {
     expect(body.outputDimensionality).toBe(768);
   });
 
+  it("uses custom outputDimensionality for each embedBatch request", async () => {
+    const fetchMock = createGeminiBatchFetchMock(2);
+    vi.stubGlobal("fetch", fetchMock);
+    mockResolvedProviderKey();
+
+    const { provider } = await createGeminiEmbeddingProvider({
+      config: {} as never,
+      provider: "gemini",
+      model: "gemini-embedding-2-preview",
+      fallback: "none",
+      outputDimensionality: 768,
+    });
+
+    await provider.embedBatch(["text1", "text2"]);
+
+    const body = parseFetchBody(fetchMock);
+    expect(body.requests).toEqual([
+      expect.objectContaining({ outputDimensionality: 768 }),
+      expect.objectContaining({ outputDimensionality: 768 }),
+    ]);
+  });
+
   it("throws for invalid outputDimensionality", async () => {
     mockResolvedProviderKey();
 
diff --git a/src/memory/embeddings-gemini.ts b/src/memory/embeddings-gemini.ts
index 3aa13d798f2..f8c3d3f4a06 100644
--- a/src/memory/embeddings-gemini.ts
+++ b/src/memory/embeddings-gemini.ts
@@ -53,6 +53,12 @@ export type GeminiFilePart = {
   fileData: { mimeType: string; fileUri: string };
 };
 export type GeminiPart = GeminiTextPart | GeminiInlinePart | GeminiFilePart;
+export type GeminiTextEmbeddingRequest = {
+  content: { parts: GeminiTextPart[] };
+  taskType: GeminiTaskType;
+  outputDimensionality?: number;
+  model?: string;
+};
 
 /** Convert a string or pre-built parts array into `GeminiPart[]`. */
 export function buildGeminiParts(input: string | GeminiPart[]): GeminiPart[] {
@@ -72,6 +78,26 @@ export function buildFileDataPart(mimeType: string, fileUri: string): GeminiFile
   return { fileData: { mimeType, fileUri } };
 }
 
+/** Builds the text-only Gemini embedding request shape used across direct and batch APIs. */
+export function buildGeminiTextEmbeddingRequest(params: {
+  text: string;
+  taskType: GeminiTaskType;
+  outputDimensionality?: number;
+  modelPath?: string;
+}): GeminiTextEmbeddingRequest {
+  const request: GeminiTextEmbeddingRequest = {
+    content: { parts: [{ text: params.text }] },
+    taskType: params.taskType,
+  };
+  if (params.modelPath) {
+    request.model = params.modelPath;
+  }
+  if (params.outputDimensionality != null) {
+    request.outputDimensionality = params.outputDimensionality;
+  }
+  return request;
+}
+
 /**
  * Returns true if the given model name is a gemini-embedding-2 variant that
  * supports `outputDimensionality` and extended task types.
@@ -186,13 +212,11 @@ export async function createGeminiEmbeddingProvider(
     if (!text.trim()) {
       return [];
     }
-    const body: Record<string, unknown> = {
-      content: { parts: [{ text }] },
+    const body = buildGeminiTextEmbeddingRequest({
+      text,
       taskType: options.taskType ?? "RETRIEVAL_QUERY",
-    };
-    if (isV2 && outputDimensionality != null) {
-      body.outputDimensionality = outputDimensionality;
-    }
+      outputDimensionality: isV2 ? outputDimensionality : undefined,
+    });
     const payload = await executeWithApiKeyRotation({
       provider: "google",
       apiKeys: client.apiKeys,
@@ -205,18 +229,15 @@ export async function createGeminiEmbeddingProvider(
     if (texts.length === 0) {
       return [];
     }
-    const requests = texts.map((text) => {
-      const req: Record<string, unknown> = {
-        model: client.modelPath,
-        content: { parts: [{ text }] },
+    const requests = texts.map((text) =>
+      buildGeminiTextEmbeddingRequest({
+        text,
+        modelPath: client.modelPath,
         taskType: options.taskType ?? "RETRIEVAL_DOCUMENT",
-      };
-      if (isV2 && outputDimensionality != null) {
-        req.outputDimensionality = outputDimensionality;
-      }
-      return req;
-    });
-    const batchBody: Record<string, unknown> = { requests };
+        outputDimensionality: isV2 ? outputDimensionality : undefined,
+      }),
+    );
+    const batchBody = { requests };
     const payload = await executeWithApiKeyRotation({
       provider: "google",
       apiKeys: client.apiKeys,
diff --git a/src/memory/manager-embedding-ops.ts b/src/memory/manager-embedding-ops.ts
index 97a26dcc315..bcc653fda7a 100644
--- a/src/memory/manager-embedding-ops.ts
+++ b/src/memory/manager-embedding-ops.ts
@@ -9,6 +9,7 @@ import {
 import { type VoyageBatchRequest, runVoyageEmbeddingBatches } from "./batch-voyage.js";
 import { enforceEmbeddingMaxInputTokens } from "./embedding-chunk-limits.js";
 import { estimateUtf8Bytes } from "./embedding-input-limits.js";
+import { buildGeminiTextEmbeddingRequest } from "./embeddings-gemini.js";
 import {
   chunkMarkdown,
   hashText,
@@ -482,9 +483,11 @@ export abstract class MemoryManagerEmbeddingOps extends MemoryManagerSyncOps {
       provider: "gemini",
       enabled: Boolean(gemini),
       buildRequest: (chunk) => ({
-        content: { parts: [{ text: chunk.text }] },
-        taskType: "RETRIEVAL_DOCUMENT",
-        outputDimensionality: this.gemini?.outputDimensionality,
+        request: buildGeminiTextEmbeddingRequest({
+          text: chunk.text,
+          taskType: "RETRIEVAL_DOCUMENT",
+          outputDimensionality: this.gemini?.outputDimensionality,
+        }),
       }),
       runBatch: async (runnerOptions) =>
         await runGeminiEmbeddingBatches({